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The emergence of large scale Big Data projects continue to grow. This has fuelled the need to process Big Data faster and is accelerating the adoption of new approaches and technologies. One such technology exploding in 2015 is Apache Spark. According to IBM this is a crucial technology that will make it possible to quickly gain insights from data. This will produce extraordinary time and cost savings and will enable early adopters to thereby save time and spot opportunities in areas like sales and new product development at an unprecedented rate.
CIO published an article that said “the primary mission of the CIO is no longer to drive competitive advantage by balancing a cadence of enterprise-wide deployments with the ongoing maintenance of legacy infrastructure.” Instead it suggested that “the best CIOs will embrace public cloud technology, free themselves from infrastructure maintenance, and instead focus on ways to increase employee and customer engagement that drive business results.”
The majority of enterprises are looking into the deployment of multiple clouds for both the short and long-term according to survey results reported in Cloud Tech News. The research found that:
Say you have deployed a multi-tier web application in the cloud, with each tier made up of a few servers. How large does each tier need to be? That depends on the demand placed on the application at any given time, and in many cases this is hard, if not impossible, to predict. Each tier may have its own internal bottlenecks and will have to scale differently from the others. But in any case, it all boils down to:
Too little server resource and your application user’s experience will suffer;
Too much and you are over provisioning and over spending on infrastructure.